{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Link prediction with Metapath2Vec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "source": [
    "<table><tr><td>Run the latest release of this notebook:</td><td><a href=\"https://mybinder.org/v2/gh/stellargraph/stellargraph/master?urlpath=lab/tree/demos/link-prediction/metapath2vec-link-prediction.ipynb\" alt=\"Open In Binder\" target=\"_parent\"><img src=\"https://mybinder.org/badge_logo.svg\"/></a></td><td><a href=\"https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/link-prediction/metapath2vec-link-prediction.ipynb\" alt=\"Open In Colab\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a></td></tr></table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "This demo notebook demonstrates how to predict friendship links/edges between users in the Blog Catalog dataset using Metapath2Vec. Metapath2Vec is a useful algorithm that allows us to run random walks on a heterogeneous graph (with multiple node types) by defining \"metapaths\" which tell the algorithm how to traverse the different node types that exist in the graph.\n",
    "\n",
    "Using Metapath2Vec, we're going to tackle link prediction as a supervised learning problem on top of node representations/embeddings. After obtaining embeddings via the unsupervised algorithm, a binary classifier can be used to predict a link, or not, between any two nodes in the graph. Various hyperparameters could be relevant in obtaining the best link classifier - this demo demonstrates incorporating model selection into the pipeline for choosing the best binary operator to apply on a pair of node embeddings.\n",
    "\n",
    "There are four steps:\n",
    "\n",
    "1. Obtain embeddings for each node\n",
    "2. For each set of hyperparameters, train a classifier\n",
    "3. Select the classifier that performs the best\n",
    "4. Evaluate the selected classifier on unseen data to validate its ability to generalise\n",
    "\n",
    "> StellarGraph supports other algorithms for doing [link prediction](README.md), as well as many [other tasks](../README.md) such as [node classification](../node-classification/README.md), and [representation learning](../embeddings/README.md).\n",
    "\n",
    "### References\n",
    "\n",
    "[1] Metapath2Vec: Scalable Representation Learning for Heterogeneous Networks. Y. Dong, N. Chawla, A. Swami, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.\n",
    "\n",
    "[2] Node2Vec: Scalable Feature Learning for Networks. A. Grover, J. Leskovec. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "outputs": [],
   "source": [
    "# install StellarGraph if running on Google Colab\n",
    "import sys\n",
    "if 'google.colab' in sys.modules:\n",
    "  %pip install -q stellargraph[demos]==1.2.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "VersionCheck"
    ]
   },
   "outputs": [],
   "source": [
    "# verify that we're using the correct version of StellarGraph for this notebook\n",
    "import stellargraph as sg\n",
    "\n",
    "try:\n",
    "    sg.utils.validate_notebook_version(\"1.2.1\")\n",
    "except AttributeError:\n",
    "    raise ValueError(\n",
    "        f\"This notebook requires StellarGraph version 1.2.1, but a different version {sg.__version__} is installed.  Please see <https://github.com/stellargraph/stellargraph/issues/1172>.\"\n",
    "    ) from None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from math import isclose\n",
    "from sklearn.decomposition import PCA\n",
    "import os\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from stellargraph import StellarGraph, datasets\n",
    "from stellargraph.data import EdgeSplitter\n",
    "from collections import Counter\n",
    "import multiprocessing\n",
    "from IPython.display import display, HTML\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the dataset\n",
    "\n",
    "The Blog Catalog 3 dataset is a heterogeneous network with two different node types - `user` and `group`. Two `user` nodes can be connected via a `friend` edge type (i.e. two users are friends), and a `user` can also be connected to a `group` via a `belongs` edge type (i.e. user belongs to group). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "This dataset is crawled from a social blog directory website BlogCatalog http://www.blogcatalog.com and contains the friendship network crawled and group memberships."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = datasets.BlogCatalog3()\n",
    "display(HTML(dataset.description))\n",
    "graph = dataset.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "StellarGraph: Undirected multigraph\n",
      " Nodes: 10351, Edges: 348459\n",
      "\n",
      " Node types:\n",
      "  user: [10312]\n",
      "    Features: none\n",
      "    Edge types: user-belongs->group, user-friend->user\n",
      "  group: [39]\n",
      "    Features: none\n",
      "    Edge types: group-belongs->user\n",
      "\n",
      " Edge types:\n",
      "    user-friend->user: [333983]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n",
      "    user-belongs->group: [14476]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n"
     ]
    }
   ],
   "source": [
    "print(graph.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Construct splits of the input data\n",
    "\n",
    "We have to carefully split the data to avoid data leakage and evaluate the algorithms correctly:\n",
    "\n",
    "* For computing node embeddings, a **Train Graph** (`graph_train`)\n",
    "* For training classifiers, a classifier **Training Set** (`examples_train`) of positive and negative edges that weren't used for computing node embeddings\n",
    "* For choosing the best classifier, an **Model Selection Test Set** (`examples_model_selection`) of positive and negative edges that weren't used for computing node embeddings or training the classifier \n",
    "* For the final evaluation, a **Test Graph** (`graph_test`) to compute test node embeddings with more edges than the Train Graph, and a **Test Set** (`examples_test`) of positive and negative edges not used for neither computing the test node embeddings or for classifier training or model selection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Test Graph\n",
    "\n",
    "We begin with the full graph and use the `EdgeSplitter` class to produce:\n",
    "\n",
    "* Test Graph\n",
    "* Test set of positive/negative link examples\n",
    "\n",
    "The Test Graph is the reduced graph we obtain from removing the test set of links from the full graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network has 333983 edges of type friend\n",
      "Network has 333983 edges of type friend\n",
      "** Sampled 33398 positive and 33398 negative edges. **\n",
      "StellarGraph: Undirected multigraph\n",
      " Nodes: 10351, Edges: 315061\n",
      "\n",
      " Node types:\n",
      "  user: [10312]\n",
      "    Features: none\n",
      "    Edge types: user-belongs->group, user-friend->user\n",
      "  group: [39]\n",
      "    Features: none\n",
      "    Edge types: group-belongs->user\n",
      "\n",
      " Edge types:\n",
      "    user-friend->user: [300585]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n",
      "    group-belongs->user: [14476]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n"
     ]
    }
   ],
   "source": [
    "# Define an edge splitter on the original graph:\n",
    "edge_splitter_test = EdgeSplitter(graph)\n",
    "\n",
    "# Randomly sample a fraction p=0.1 of all positive links, and same number of negative links, from graph, and obtain the\n",
    "# reduced graph graph_test with the sampled links removed:\n",
    "graph_test, examples_test, labels_test = edge_splitter_test.train_test_split(\n",
    "    p=0.1, method=\"global\", edge_label=\"friend\"\n",
    ")\n",
    "\n",
    "print(graph_test.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train Graph\n",
    "\n",
    "This time, we use the `EdgeSplitter` on the Test Graph, and perform a train/test split on the examples to produce:\n",
    "\n",
    "* Train Graph\n",
    "* Training set of link examples\n",
    "* Set of link examples for model selection\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Network has 300585 edges of type friend\n",
      "Network has 300585 edges of type friend\n",
      "** Sampled 30058 positive and 30058 negative edges. **\n",
      "StellarGraph: Undirected multigraph\n",
      " Nodes: 10351, Edges: 285003\n",
      "\n",
      " Node types:\n",
      "  user: [10312]\n",
      "    Features: none\n",
      "    Edge types: user-belongs->group, user-friend->user\n",
      "  group: [39]\n",
      "    Features: none\n",
      "    Edge types: group-belongs->user\n",
      "\n",
      " Edge types:\n",
      "    user-friend->user: [270527]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n",
      "    group-belongs->user: [14476]\n",
      "        Weights: all 1 (default)\n",
      "        Features: none\n"
     ]
    }
   ],
   "source": [
    "# Do the same process to compute a training subset from within the test graph\n",
    "edge_splitter_train = EdgeSplitter(graph_test, graph)\n",
    "graph_train, examples, labels = edge_splitter_train.train_test_split(\n",
    "    p=0.1, method=\"global\", edge_label=\"friend\"\n",
    ")\n",
    "(\n",
    "    examples_train,\n",
    "    examples_model_selection,\n",
    "    labels_train,\n",
    "    labels_model_selection,\n",
    ") = train_test_split(examples, labels, train_size=0.75, test_size=0.25)\n",
    "\n",
    "print(graph_train.info())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below is a summary of the different splits that have been created in this section"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Examples</th>\n",
       "      <th>Hidden from</th>\n",
       "      <th>Picked from</th>\n",
       "      <th>Use</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Split</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Training Set</th>\n",
       "      <td>45087</td>\n",
       "      <td>Train Graph</td>\n",
       "      <td>Test Graph</td>\n",
       "      <td>Train the Link Classifier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model Selection</th>\n",
       "      <td>15029</td>\n",
       "      <td>Train Graph</td>\n",
       "      <td>Test Graph</td>\n",
       "      <td>Select the best Link Classifier model</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Test set</th>\n",
       "      <td>66796</td>\n",
       "      <td>Test Graph</td>\n",
       "      <td>Full Graph</td>\n",
       "      <td>Evaluate the best Link Classifier</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Number of Examples  Hidden from Picked from  \\\n",
       "Split                                                          \n",
       "Training Set                  45087  Train Graph  Test Graph   \n",
       "Model Selection               15029  Train Graph  Test Graph   \n",
       "Test set                      66796   Test Graph  Full Graph   \n",
       "\n",
       "                                                   Use  \n",
       "Split                                                   \n",
       "Training Set                 Train the Link Classifier  \n",
       "Model Selection  Select the best Link Classifier model  \n",
       "Test set             Evaluate the best Link Classifier  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(\n",
    "    [\n",
    "        (\n",
    "            \"Training Set\",\n",
    "            len(examples_train),\n",
    "            \"Train Graph\",\n",
    "            \"Test Graph\",\n",
    "            \"Train the Link Classifier\",\n",
    "        ),\n",
    "        (\n",
    "            \"Model Selection\",\n",
    "            len(examples_model_selection),\n",
    "            \"Train Graph\",\n",
    "            \"Test Graph\",\n",
    "            \"Select the best Link Classifier model\",\n",
    "        ),\n",
    "        (\n",
    "            \"Test set\",\n",
    "            len(examples_test),\n",
    "            \"Test Graph\",\n",
    "            \"Full Graph\",\n",
    "            \"Evaluate the best Link Classifier\",\n",
    "        ),\n",
    "    ],\n",
    "    columns=(\"Split\", \"Number of Examples\", \"Hidden from\", \"Picked from\", \"Use\"),\n",
    ").set_index(\"Split\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Metapath2Vec\n",
    "\n",
    "We use Metapath2Vec [1], to calculate node embeddings. These embeddings are learned in such a way to ensure that nodes that are close in the graph remain close in the embedding space. Similar to Node2Vec [2], we first run random walks which are used to generate context pairs, and these are fed into a Word2Vec model to generate embeddings.\n",
    "\n",
    "The random walks in Metapath2Vec are driven by a set of metapaths that define the node type order by which the random walk explores the graph. For example, a metapath like `[\"user\", \"group\", \"user\"]` can be interpreted as a rule for the random walk to always traverse the graph starting from a `user` node -> `group` node -> `user` node. Some things to keep in mind when defining metapaths are:\n",
    "\n",
    "* Each metapath must begin and end on the same node type, which must be the node type that you intend to obtain embeddings for. \n",
    "* When `walk_length` is greater than the length of a metapath, the metapath is automatically repeated to fill the length of the walk.\n",
    "* The graph should have edge types that connect two adjacent nodes in a metapath. For example, for Blog Catalog 3, there aren't any edge types connecting two `group` nodes, so `[\"group, \"group\"]` will not be a useful metapath.\n",
    "\n",
    "These are the set of parameters we can use:\n",
    "\n",
    "* `dimensions` - Dimensionality of node2vec embeddings\n",
    "* `num_walks` - Number of walks from each node\n",
    "* `walk_length` - Length of each random walk\n",
    "* `context_window_size` - Context window size for Word2Vec\n",
    "* `num_iter` - number of SGD iterations (epochs)\n",
    "* `workers` - Number of workers for Word2Vec\n",
    "* `user_metapaths` - A list of metapaths for the random walks to traverse in the graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "dimensions = 128\n",
    "num_walks = 1\n",
    "walk_length = 100\n",
    "context_window_size = 10\n",
    "num_iter = 1\n",
    "workers = multiprocessing.cpu_count()\n",
    "user_metapaths = [\n",
    "    [\"user\", \"group\", \"user\"],\n",
    "    [\"user\", \"group\", \"user\", \"user\"],\n",
    "    [\"user\", \"user\"],\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from stellargraph.data import UniformRandomMetaPathWalk\n",
    "from gensim.models import Word2Vec\n",
    "\n",
    "\n",
    "def metapath2vec_embedding(graph, name):\n",
    "    rw = UniformRandomMetaPathWalk(graph)\n",
    "    walks = rw.run(\n",
    "        graph.nodes(), n=num_walks, length=walk_length, metapaths=user_metapaths\n",
    "    )\n",
    "    print(f\"Number of random walks for '{name}': {len(walks)}\")\n",
    "\n",
    "    model = Word2Vec(\n",
    "        walks,\n",
    "        size=dimensions,\n",
    "        window=context_window_size,\n",
    "        min_count=0,\n",
    "        sg=1,\n",
    "        workers=workers,\n",
    "        iter=num_iter,\n",
    "    )\n",
    "\n",
    "    def get_embedding(u):\n",
    "        return model.wv[u]\n",
    "\n",
    "    return get_embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of random walks for 'Train Graph': 30936\n"
     ]
    }
   ],
   "source": [
    "embedding_train = metapath2vec_embedding(graph_train, \"Train Graph\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train and evaluate the link prediction model\n",
    "\n",
    "There are a few steps involved in using the Word2Vec model to perform link prediction:\n",
    "1. We calculate link/edge embeddings for the positive and negative edge samples by applying a binary operator on the embeddings of the source and target nodes of each sampled edge.\n",
    "2. Given the embeddings of the positive and negative examples, we train a logistic regression classifier to predict a binary value indicating whether an edge between two nodes should exist or not.\n",
    "3. We evaluate the performance of the link classifier for each of the 4 operators on the training data with node embeddings calculated on the **Train Graph** (`graph_train`), and select the best classifier.\n",
    "4. The best classifier is then used to calculate scores on the test data with node embeddings calculated on the **Test Graph** (`graph_test`).\n",
    "\n",
    "Below are a set of helper functions that let us repeat these steps for each of the binary operators."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.linear_model import LogisticRegressionCV\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "\n",
    "# 1. link embeddings\n",
    "def link_examples_to_features(link_examples, transform_node, binary_operator):\n",
    "    return [\n",
    "        binary_operator(transform_node(src), transform_node(dst))\n",
    "        for src, dst in link_examples\n",
    "    ]\n",
    "\n",
    "\n",
    "# 2. training classifier\n",
    "def train_link_prediction_model(\n",
    "    link_examples, link_labels, get_embedding, binary_operator\n",
    "):\n",
    "    clf = link_prediction_classifier()\n",
    "    link_features = link_examples_to_features(\n",
    "        link_examples, get_embedding, binary_operator\n",
    "    )\n",
    "    clf.fit(link_features, link_labels)\n",
    "    return clf\n",
    "\n",
    "\n",
    "def link_prediction_classifier(max_iter=2000):\n",
    "    lr_clf = LogisticRegressionCV(Cs=10, cv=10, scoring=\"roc_auc\", max_iter=max_iter)\n",
    "    return Pipeline(steps=[(\"sc\", StandardScaler()), (\"clf\", lr_clf)])\n",
    "\n",
    "\n",
    "# 3. and 4. evaluate classifier\n",
    "def evaluate_link_prediction_model(\n",
    "    clf, link_examples_test, link_labels_test, get_embedding, binary_operator\n",
    "):\n",
    "    link_features_test = link_examples_to_features(\n",
    "        link_examples_test, get_embedding, binary_operator\n",
    "    )\n",
    "    score = evaluate_roc_auc(clf, link_features_test, link_labels_test)\n",
    "    return score\n",
    "\n",
    "\n",
    "def evaluate_roc_auc(clf, link_features, link_labels):\n",
    "    predicted = clf.predict_proba(link_features)\n",
    "\n",
    "    # check which class corresponds to positive links\n",
    "    positive_column = list(clf.classes_).index(1)\n",
    "    return roc_auc_score(link_labels, predicted[:, positive_column])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We consider 2 different operators: \n",
    "\n",
    "* $L_1$\n",
    "* $L_2$\n",
    "\n",
    "The Node2Vec paper [2] provides a detailed description of these operators. All operators produce link embeddings that have equal dimensionality to the input node embeddings (128 dimensions for our example). \n",
    "\n",
    "Note that the `hadamard` and `average` operators from the reference paper has been omitted from this demo, since they aren't able to handle the case where two different sets of embeddings (`train` and `test`) have been calculated independently. With two different sets of embeddings, we want the operator to calculate some sort of relationship between a pair of embeddings rather than draw meaning from their specific values, so these two operators are not well suited for this situation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def operator_l1(u, v):\n",
    "    return np.abs(u - v)\n",
    "\n",
    "\n",
    "def operator_l2(u, v):\n",
    "    return (u - v) ** 2\n",
    "\n",
    "\n",
    "def run_link_prediction(binary_operator):\n",
    "    clf = train_link_prediction_model(\n",
    "        examples_train, labels_train, embedding_train, binary_operator\n",
    "    )\n",
    "    score = evaluate_link_prediction_model(\n",
    "        clf,\n",
    "        examples_model_selection,\n",
    "        labels_model_selection,\n",
    "        embedding_train,\n",
    "        binary_operator,\n",
    "    )\n",
    "\n",
    "    return {\n",
    "        \"classifier\": clf,\n",
    "        \"binary_operator\": binary_operator,\n",
    "        \"score\": score,\n",
    "    }\n",
    "\n",
    "\n",
    "binary_operators = [operator_l1, operator_l2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best result from 'operator_l2'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROC AUC score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>operator_l1</th>\n",
       "      <td>0.826110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>operator_l2</th>\n",
       "      <td>0.831046</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ROC AUC score\n",
       "name                      \n",
       "operator_l1       0.826110\n",
       "operator_l2       0.831046"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = [run_link_prediction(op) for op in binary_operators]\n",
    "best_result = max(results, key=lambda result: result[\"score\"])\n",
    "\n",
    "print(f\"Best result from '{best_result['binary_operator'].__name__}'\")\n",
    "\n",
    "pd.DataFrame(\n",
    "    [(result[\"binary_operator\"].__name__, result[\"score\"]) for result in results],\n",
    "    columns=(\"name\", \"ROC AUC score\"),\n",
    ").set_index(\"name\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluate the best model using the test set\n",
    "\n",
    "Now that we've trained and selected our best model, we use a test set of embeddings and calculate a final evaluation score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of random walks for 'Test Graph': 30936\n"
     ]
    }
   ],
   "source": [
    "embedding_test = metapath2vec_embedding(graph_test, \"Test Graph\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score on test set using 'operator_l2': 0.7389910535953208\n"
     ]
    }
   ],
   "source": [
    "test_score = evaluate_link_prediction_model(\n",
    "    best_result[\"classifier\"],\n",
    "    examples_test,\n",
    "    labels_test,\n",
    "    embedding_test,\n",
    "    best_result[\"binary_operator\"],\n",
    ")\n",
    "print(\n",
    "    f\"ROC AUC score on test set using '{best_result['binary_operator'].__name__}': {test_score}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualise representations of link embeddings\n",
    "\n",
    "Learned link embeddings have 128 dimensions but for visualisation we project them down to 2 dimensions using the PCA algorithm ([link](https://en.wikipedia.org/wiki/Principal_component_analysis)). \n",
    "\n",
    "Blue points represent positive edges and red points represent negative (no edge should exist between the corresponding vertices) edges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1582be250>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate edge features for test data\n",
    "link_features = link_examples_to_features(\n",
    "    examples_test, embedding_test, best_result[\"binary_operator\"]\n",
    ")\n",
    "\n",
    "# Learn a projection from 128 dimensions to 2\n",
    "pca = PCA(n_components=2)\n",
    "X_transformed = pca.fit_transform(link_features)\n",
    "\n",
    "# plot the 2-dimensional points\n",
    "plt.figure(figsize=(16, 12))\n",
    "plt.scatter(\n",
    "    X_transformed[:, 0],\n",
    "    X_transformed[:, 1],\n",
    "    c=np.where(labels_test == 1, \"b\", \"r\"),\n",
    "    alpha=0.5,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example has demonstrated how to use the `stellargraph` library to apply a link prediction algorithm for heterogeneous graphs using the Metapath2Vec [1] representation learning algorithm.\n",
    "\n",
    "This notebook ran through the following steps:\n",
    "\n",
    "1. Obtained embeddings for each node\n",
    "2. Trained a classifier for each set of hyperparameters\n",
    "3. Selected the classifier that performed best\n",
    "4. Evaluated the selected classifier on unseen data to validate its ability to generalise\n",
    "\n",
    "StellarGraph includes [other algorithms for link prediction](README.md) and [algorithms and demos for other tasks](../README.md)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden",
    "tags": [
     "CloudRunner"
    ]
   },
   "source": [
    "<table><tr><td>Run the latest release of this notebook:</td><td><a href=\"https://mybinder.org/v2/gh/stellargraph/stellargraph/master?urlpath=lab/tree/demos/link-prediction/metapath2vec-link-prediction.ipynb\" alt=\"Open In Binder\" target=\"_parent\"><img src=\"https://mybinder.org/badge_logo.svg\"/></a></td><td><a href=\"https://colab.research.google.com/github/stellargraph/stellargraph/blob/master/demos/link-prediction/metapath2vec-link-prediction.ipynb\" alt=\"Open In Colab\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\"/></a></td></tr></table>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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